Reducing equalizer error propagation with a low complexity soft output Viterbi decoder

ABSTRACT

Novel systems and methods are described in which performance of equalizers can be improved by reducing the effects of error propagation in equalizers that use a Viterbi Decoder. Systems and methods of symbol correction in prediction decision feedback equalization architectures are described including systems and methods that include an enhanced Viterbi decoder and novel methods of symbol correction to obtain better system performance. The use of a blending algorithm is described to reduce errors in symbol decoding. Histories of deep trace back depth symbols can be maintained to enable more accurate decisions. Systems and methods described can provide advantage in the feedback path of adaptive equalizers in trellis decoders. The invention provides novel techniques for improving the performance of equalizers by reducing the effects of error propagation in equalizers that use a Viterbi Decoder.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is related to U.S. Non-Provisional Application Ser. No.______, entitled “DUAL PDFE SYSTEM WITH FORWARD-BACKWARD VITERBI” andfiled on Apr. 17, 2006, which application is incorporated herein byreference and for all purposes.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to decoding of trellis-encoded signals andmore particularly to systems and methods of symbol correction inprediction decision feedback equalization architectures

2. Description of Related Art

Since the adoption of the Advanced Television Systems Committee (“ATSC”)digital television (“DTV”) standard in 1996, there has been an ongoingeffort to improve the design of receivers built for the ATSC DTV signalas described in the ATSC standard A/54 (see U.S. patent applicationpublication 20050163209 for . . . ). Designers face major obstacles indesigning receivers that might achieve good reception in the presence ofmultipath interference in the channel. Multipath interference affectsthe ability of the receiver to correctly decode transmitted symbols.Therefore, designers often add equalizers to receivers in order tocancel the effects of multipath interference and thereby improve signalreception.

Referring to FIG. 1, in the ATSC DTV transmission system, data istransmitted in frames 10. Each frame 10 is composed of 2 fields 11 and12, each field 11 and 12 having 313 segments, and each segment having832 symbols. The first four symbols in each segment are segment syncsymbols 13 having the sequence [+5, −5, −5, +5]. The first segment ineach field is a field sync segment 14 and 15.

Referring to figure shown in more detail in FIG. 2, field sync 20comprises segment sync 21, a 511 symbol pseudo noise (PN511) sequence22, a 63 symbol pseudo noise (PN63) sequence 23, a second PN63 sequence24, a third PN63 sequence 25, and a 128 symbol sequence 26 composed ofvarious mode, reserved, and precode symbols. The four PN sequences 22-25are composed of symbols from the set {+5, −5}. In alternate fields, thethree PN63 sequences 23-25 are the same. In the remaining fields, thefirst PN63 23 and third PN63 25 are the same while the second PN63 24 isinverted.

As shown in FIG. 3, subsequent 312 segments 30 of the field 11 and 12(referred to as data segments) are structured such that 828 symbols 32following the four segment sync symbols 31 are trellis encoded by a 12phase trellis encoder described in detail in ATSC standard A/54. Thisresults in 8 level symbols derived from the alphabet {−7 −5 −3 −1 +1 +3+5 +7}.

Consider now an 8T-VSB transmitter such as is illustrated in FIG. 4.Input data 40 is first randomized 41, Reed-Solomon byte wise encoded 42,and then byte interleaved 43. Next the data is trellis encoded by a12-phase trellis encoder 44. A multiplexer 45 adds the segment syncsymbols and the field sync symbols to the trellis coded data at theappropriate times in the frame. Then, a pilot is inserted 46 by adding aDC level to the baseband signal and a modulator 47 modulates theresulting symbols to IF. Finally a RF upconverter 48 converts the signalfor RF transmission as a vestigial sideband (VSB) signal at a symbolrate of 10.76 MHz.

Now consider a baseband model of the transmission channel fed by theabove transmitter. The transmitted signal has a root raised cosinespectrum with a nominal bandwidth of 5.38 MHz and an excess bandwidth of11.5% centered at one fourth of the symbol rate (i.e., 2.69 MHz). Thusthe transmitted pulse shape q(t) is complex and given byq(t)=e ^(jπF) ^(x) ^(t/2) q _(RRC) ^((t)),where F_(s) is the symbol frequency, and q_(RRC)(t) is a real squareroot raised cosine pulse with an excess bandwidth of 11.5% of thechannel. The pulse q(t) is referred to as the “complex root raisedcosine pulse”. For the 8T-VSB system, the transmitter pulse shape q(t)and the receiver matched filter pulse shape q*(−t) are identical sinceq(t) is conjugate-symmetric. Thus the raised cosine pulse p(t), referredto as the “complex raised cosine pulse”, is given byp(t)=q(t)*q*(−t)where * denotes convolution, and * denotes complex conjugation. Thetransmitted baseband signal of data rate 1/T symbols/sec can berepresented as:${{s(t)} = {\sum\limits_{k}{I_{k}{q( {t - {kT}} )}}}},$where {I_(k) ∈ A≡{α₁, . . . α₈}⊂R¹} is the transmitted data sequence,which is a discrete 8-ary sequence taking values on the real 8-aryalphabet A. The physical channel between the transmitter and receiver isdenoted c(t) and can be described by:${c(t)} = {\sum\limits_{k = {- L_{ha}}}^{L_{hc}}{c_{k}{\delta( {t - \tau_{k}} )}}}$where {c_(k)(τ)}⊂C¹, L_(ha) and L_(hc) are the number of maximumanti-casual and casual multipath delays, τ_(k) is multipath delay, andδ(t) is the Dirac delta function. Hence, the overall channel impulseresponse is${h(t)} = {{{p(t)}*{c(t)}} = {\sum\limits_{- L_{ha}}^{L_{hc}}{c_{k}{p( {t - \tau_{k}} )}}}}$

FIG. 5 shows an 8T-VSB receiver block diagram. A tuner 50 and IF filter51 demodulate an RF signal to baseband. Next, timing and synchronizationrecovery is performed 52 along with the rejection of any NTSCinterference 53. The data is then equalized 54 and sent through a phasetracker 55 and trellis decoded 56, de-interleaved 57, Reed-Solomondecoded 58, and finally de-randomized 59. The matched filter output y(t)in the receiver prior to equalization is:${{y(t)} = {{( {\sum\limits_{k}{\delta( {t - {kT}} )}} )*{h(t)}} + {v(t)}}},$wherev(t)=η(t)*q*(−t)denotes the complex (colored) noise process after the pulse matchedfilter, with η(t) being a zero-mean white Gaussian noise process withspectral density σ_(n) ² per real and imaginary part. Sampling thematched filter output y(t) at the symbol rate produces the discrete timerepresentation of the overall communication system according to thefollowing equation:y[n]≡y(t)|_(t=nT) =ΣI _(k) h[n−k]+v[n]

Broadcast television channels are a relatively severe multipathenvironment due to a variety of conditions encountered in the channeland at the receiver. Only 728 symbols of a VSB field sync segment areknown a priori and can be used as a training sequence for an adaptiveequalizer. The channel is not known a priori, so the equalizer in thereceiver must be able to adaptively identify and combat the variouschannel conditions. Since multipath signals in the broadcast channel mayarrive many symbols after the main signal, the decision feedbackequalizer (DFE) is invariably used in 8T-VSB applications. Another DFEstructure that is well known is the noise predictive decision feedbackequalizer (pDFE). Although both DFEs and pDFEs are good at combatingmultipath channels, both have the problem of error propagation. Errorpropagation occurs when there are errors in the feedback path. This, inturn, feeds erroneous data into the decision device resulting inincorrect symbol decisions. For 8T-VSB applications, the most commonlyused decision device is the Viterbi Decoder. Therefore it is importantto mitigate the effects of error propagation.

Since the 8T-VSB symbols are convolutionally coded, they may be decodedin the receiver with a Viterbi decoder [ATSC Standard A/54, U.S. Pat.No. 5,600,677, U.S. Pat. No. 5,583,889]. The Viterbi Algorithm (VA) formaximum likelihood sequence estimation of transmitted symbols corruptedby white noise is very well known (see “The Viterbi Algorithm”, G. D.Forney, Jr., Proc. IEEE, vol. 61, pp. 268 -278, March 1973, “DigitalCommunications—Fundamentals and Applications”, Bernard Sklar,Prentice-Hall, 1988). The decoder may equivalently provide estimates ofthe encoded bit pairs or estimates of the mapped 8 level symbols, thelater being utilized in the context of an equalizer. As is well known,the VA requires a path history memory for each state and involves add,compare, select operations based on trellis path metrics determined fromsums of Euclidean distance branch metrics. As time advances, the mostlikely trellis paths (as indicated by the lowest path metrics) into eachstate of the trellis are saved, the rest are discarded. If the decodingalgorithm searches back sufficiently deep in the trellis path memory,the result of discarding less likely paths—leaving only survivorpaths—is a single surviving branch which defines the most likely symbol(hard symbol decision) at that prior point in time. At shallower pathmemory trace back depths (closer to the present time), there is a higherlikelihood of multiple surviving branches with symbol probabilitiesproportional to the corresponding path metrics.

BRIEF SUMMARY OF THE INVENTION

The present invention provides a novel technique for improving theperformance of equalizers by reducing the effects of error propagationin equalizers that use a Viterbi Decoder. Systems and methods of symbolcorrection in prediction decision feedback equalization (“pDFE”)architectures are provided. Particularly, embodiments of the inventionare described that include an enhanced Viterbi decoder and novel methodsof symbol correction to obtain better system performance. The use of ablending algorithm is described to reduce errors in symbol decoding.

The Viterbi Algorithm (“VA”) can be described as follows for an S statetrellis with a path memory of length M for each state that holds asequence of state transitions and associated branch metrics:

-   -   At each time increment n.    -   For each trellis state k.    -   Calculate the Euclidean branch metric for each branch into state        k from all possible prior states at time (n−1).    -   Add the above branch metrics to the associated path metrics for        each possible prior state at time (n−1).    -   Choose the path into state k at time n with the best path metric        and store it in the path memory associated with state k        (overwriting the previous stored path).    -   Decode symbol.    -   Examine path memory back to time (n-M); if M is large enough,        the path memories for each of the S states will show the same        state transition at time (n-M) and hence indicate the same        symbol; choose that symbol as the hard decision.    -   If the state transitions for time (n-M) are not the same, choose        the state transition (and hence the symbol) corresponding to the        path that has the best path metric from time (n-M) to time n.        Instead of outputting a single symbol decision delayed by M, the        decoder can output a M+1 long vector of symbol decisions with        delays ranging from zero (corresponding to time n) to M as        follows. For each time increment n, the Viterbi decoder updates        the metrics and returns a vector of symbols whose length is M+1,        where M is referred to as the trace back depth. As described        above, the deep trace back depth symbol decisions will be more        accurate than the shallow trace back depth symbols.

As will be explained in more detail below, trellis decoders may use thisadvantage in the feedback path of an adaptive equalizer. For a giventime n, it can be beneficial to update all M+1 symbols in the equalizerfeedback path such that M trace back depth symbols can overwrite Mpreviously decoded symbols in the feedback path, thereby updating symboldecisions for times (n-M) through n. Such updating of more accuratesymbols can facilitate a reduction in error propagation in the equalizerfeedback path. Consequently, the present invention provides noveltechniques for improving the performance of equalizers by reducing theeffects of error propagation in equalizers that use a Viterbi Decoder.

The foregoing and other aspects of various embodiments of the presentinvention will be apparent through examination of the following detaileddescription thereof in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and notlimitation, in the figures of the accompanying drawings in which likereferences denote similar elements, and in which:

FIG. 1 depicts a frame in an ATSC DTV transmission system;

FIG. 2 depicts a field sync segment in a frame in an ATSC DTVtransmission system;

FIG. 3 depicts a data segment in a frame in an ATSC DTV transmissionsystem;

FIG. 4 illustrates an 8T-VSB transmitter;

FIG. 5 shows an 8T-VSB receiver block diagram;

FIG. 6 illustrates prediction decision feedback equalization as includedin certain embodiments of the invention; and

FIG. 7 is an example of a system according to one embodiment of theinvention.

DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the present invention will now be described in detailwith reference to the drawings, which are provided as illustrativeexamples so as to enable those skilled in the art to practice theinvention. Notably, the figures and examples below are not meant tolimit the scope of the present invention. Wherever convenient, the samereference numbers will be used throughout the drawings to refer to sameor like parts. Where certain elements of these embodiments can bepartially or fully implemented using known components, only thoseportions of such known components that are necessary for anunderstanding of the present invention will be described, and detaileddescriptions of other portions of such known components will be omittedso as not to obscure the invention. Further, the present inventionencompasses present and future known equivalents to the componentsreferred to herein by way of illustration.

Certain embodiments provide systems and methods of symbol correction inprediction decision feedback equalization (“pDFE”) architectures.Certain of the methods and systems described can also be applied toconventional decision feedback equalization (“DFE”) architectures.

Referring to FIG. 6, an example of a pDFE architecture is illustrated. Afeed forward filter 61 performs block based frequency domain filteringon data received at an input 60. Summing element 63 adds output 62 frominput filter 61 to output 69 from feedback filter 68. The summed outputis then provided to Viterbi decoder 64. Viterbi decoder 64 provides thepDFE output 65. Typically, frequency domain filter 61 is block based andoutput 65 consequently comprises a block of symbols. Output 65 is thenadded to input filter output 62 using summer 66 to provide an input 67to feedback filter 68. Feedback filter 68 can include a noise predictor(not shown). The noise predictor in the feedback loop can estimatecolored (non-white) noise from error signal 67. Adder 63 may thensubtract the estimated colored noise from the equalized data, therebyhelping Viterbi decoder 64 to make better decisions.

In certain embodiments, Viterbi Decoder 64 can store metrics for aplurality of states including a smallest metric obtained, a previousstate, and a current state. As discussed above, the metrics aretypically used to configure or adjust a Viterbi algorithm that requiresa path history memory for each state. The metrics can be based ontrellis path metrics determined from sums of Euclidean distance branchmetrics. The condition of the plurality of stored metrics is used todetermine which symbol is decoded. If a delay is incurred, ViterbiDecoder 64 may be able to correct some symbols using trace back depthdecoding.

Referring now to FIG. 7, embodiments of the invention include anenhanced Viterbi Decoder 70 as a decision device coupled with a novelmethod of symbol correction that can deliver better system performance.In certain embodiments a Viterbi algorithm operates on an S statetrellis with a path memory of length M for each state that holds asequence of state transitions and associated branch metrics and canoutput an M+1 long vector of symbol decisions with delays ranging fromzero (corresponding to time n) to M as follows. For each time incrementn, the Viterbi decoder may update the metrics and return a vector ofsymbols whose length is M+1, where M is referred to as the trace backdepth. Deep trace back depth symbol decisions can be more accurate thanshallow trace back depth symbols.

In certain embodiments, Viterbi Decoder 70 can determine metricsassociated with potential decoding paths wherein the metrics can be usedto assess reliability of decoded symbols. Viterbi Decoder 70 can outputa first vector 71 representing the most likely decoded symbols. The mostlikely symbols are typically determined by considering trace back depthdecoding. Additionally, Viterbi Decoder 70 can output a second vector 72representing second most likely decoded symbols and a difference metric(“diff_metric”) 73 quantifying a difference in estimated reliability offirst vector 71 and second vector 72. Diff_metric 73 can be used toascertain the reliability of a trellis decoded symbol such that a largediff_metric 73 value may indicate reliability of decoded symbols whilesmall a diff_metric 73 value can be indicative of decoded symbols thatare unreliable. In certain embodiments, a blender 74 can apply ablending algorithm on first vector 71 and second vector 72 based on thediff_metric 73. Having received decoded symbols from Viterbi Decoder 70,blender 74 can blend the decoded symbols with long delayed trellissymbols from Viterbi Decoder 70.

More particularly, diff_metric 73 is a measure of reliability that canbe calculated as the difference of the two smallest surviving pathmetrics. For deep trace back depth symbols, the corresponding symbols offirst vector 71 and second vector 72 can often be identical, indicatingthat a single surviving path exists at that point. However, for shallowtrace back depth symbols, it is more likely that the correspondingsymbols from first vector 71 and second vector 72 will be different,indicating that multiple surviving paths exist at that point. Pathmetrics can be calculated that indicate variances of the decoded pathfrom a measured signal path and it will be appreciated that a smallestpath metric typically indicates the most probable path. However, wheremultiple surviving paths exist, the smallest metric surviving path maygenerate errors in the decoded symbols. Diff_metric 73 can quantify theprobability of errors by indicating the difference in path metricsbetween most likely surviving paths. In the example of FIG. 7,diff_metric 73 is calculated as the difference in path metrics betweenfirst vector 71 and second vector 72.

In certain embodiments, diff_metric 73 is used to assess the reliabilityof first vector 71. A large diff_metric may be interpreted as anindication that the decoded symbols are reliable. On the other hand, asmall diff_metric may be interpreted as an indication that the decodedsymbols are unreliable. This reliability information can be provided toblender 74 for executing a blending algorithm on first vector 71 andsecond vector 72. The blending algorithm may apply weighting factorsbased on one or more successive diff-metric 73 values to generate errorcompensation in the pDFE of FIG. 7.

Referring to Table 1, an example may better illustrate weighting asemployed by blender 74 in certain embodiments. Taking a scalar weightingfactor a as weight for the most likely path while the scalar weightingfactor b weights the second most likely path. Then a and b can beselected depending on the value of diff_metric 73 as shown in Table 1.TABLE 1 1.0 < 2.0 < diff_metric <= diff_metric <= diff_metric <= 3.0 <1.0 2.0 3.0 diff_metric a 0.5 0.625 0.75 1.0 b 0.5 0.375 0.25 0.0

Consider another example in which a trace back depth of 8 is assumed.Where the symbols for the most likely path of a Viterbi Decoder are [−51 3 5 1 −3 3 −3 −7], the symbols for the second most likely path of thatsame Viterbi Decoder are [−7 −1 3 3 −1 1 3 −3 −7] and the correspondingdiff_metric 73 is 2.6. Then, according to Table 1 above, the weightingfactors are a=0.75 and b=0.25. In this example, the resulting new traceback depth decoded vector would be:0.75*[−5 1 3 5 1 −3 3 −3 −7]+0.25*[−7 −1 3 3 −1 1 3 −3 −7]=[−5.5 0.5 3.04.5 0.5 −2.0 3.0 −3.0 −7.0].This new “soft” vector can then be used in the feedback path 67-69 ofFIG. 7 instead of the most likely path vector 71. Consequently, is ableto more accurately predict the noise and improve the performance of thepDFE.

In many embodiments, implementation of the described methods of decodingsymbols can require little additional hardware. For example, the ViterbiDecoder block may be implemented using an additional M+1 memory unitsfor storing second trace back depth symbols, where M represents thetrace back depth. An adder may also be needed to calculate the diff₁₃metric. For the Blend block, three comparators, 8 preset taps (for a andb), 2M multipliers and M adders may be needed.

Simulations have been performed using the example depicted in FIG. 7,with the criterion of SER <=0.0050 for a trace back depth of 16. Sixdifferent channels were tested. In comparison to the pDFE system in FIG.6, the pDFE in FIG. 7 performs better. For Brazil A, there is a 0.1 dBimprovement (signal-to-noise ratio “SNR” input can be 0.1 dB less).Brazil B shows a 0.2 dB improvement, Brazil C shows a 0.7 dBimprovement, Brazil D shows a 0.4 dB improvement and Brazil E shows a0.9 dB improvement. This improvement incurs a minor cost in hardware.

It will be appreciated that the Brazil channels A-E are difficultmultipath channels used for reference testing. They include ghosts ofvarying delays and amplitudes. They are referenced in Interferencia porMultipercurso—Simulacao De Canais Tipo:“Rice”, “Rayleigh”, HarbourApartment” E “SNF”, SET-ABERT, Feb. 11, 1999.

It is apparent that the above embodiments may be altered in many wayswithout departing from the scope of the invention. Further, variousaspects of a particular embodiment may contain patentably subject matterwithout regard to other aspects of the same embodiment. Additionally,various aspects of different embodiments can be combined together. Also,those skilled in the art will understand that variations can be made inthe number and arrangement of components illustrated in the abovediagrams. It is intended that the appended claims include such changesand modifications.

1. A method comprising the steps of: providing a signal to a Viterbidecoder; receiving from the Viterbi Decoder a first vectorrepresentative of first decoded symbols and a second vector of seconddecoded symbols, the first vector and second vector being associatedwith corresponding measurements of reliability of the first and seconddecoded symbols; and blending selected symbols associated with thesecond vector with symbols associated with the first vector to obtain anoutput vector.
 2. The method of claim 1, wherein the step of blending isbased on reliability measurements.
 3. The method of claim 1, and furthercomprising calculating a difference metric representative of reliabilityof the output.
 4. The method of claim 3, wherein the difference metricis based on information including a history of previously decodedsymbols.
 5. The method of claim 4, and further comprising providingfeedback to the feedback filter based on the first vector, the secondvector and the corresponding measurements of reliability, wherein thefeedback is further based on the difference metric.
 6. The method ofclaim 4, and further comprising providing feedback to the feedbackfilter based on the first vector, the second vector and thecorresponding measurements of reliability, wherein the feedback includesa trace back depth decoded vector.
 7. The method of claim 3, wherein thecorresponding measurements of reliability are used to generate ablending algorithm.
 8. The method of claim 7, wherein the blendingalgorithm generates measurements by apply weighting factors based on oneor more successive difference metrics.
 9. A system for improvingequalizer performance comprising: a Viterbi decoder for providingsymbols and a corresponding difference metric; and a blender forblending most likely decoded symbols with second most likely decodedsymbols received from the Viterbi decoder based on the differencemetric.
 10. A system according to claim 9, wherein the symbols include afirst vector representing the most likely decoded symbols and a secondvector representing the second most likely decoded symbols.
 11. A systemaccording to claim 10, wherein the most likely symbols are determinedfrom trace back depth decoding.
 12. A system according to claim 11,wherein the difference metric is calculated as difference of twosmallest surviving path metrics.
 13. A system according to claim 10,wherein the trace back depth decoding employs trellis path metricsmaintained by the Viterbi decoder.
 14. A system according to claim 13,wherein the trellis path metrics are determined from sums of Euclideandistance branch metrics.
 15. An equalizer comprising: a Viterbi decoderconfigured to receive a filtered input signal adapted to provide twooutputs representing likely decoded symbols and a difference metricquantifying differences in estimated reliabilities of the two outputs;and a blender adapted to blend the likely decoded symbols with delayedtrellis symbols provided by the Viterbi decoder, wherein blending isbased on the difference metric.
 16. The equalizer of claim 15, andfurther comprising a feedback filter configured to provide a feedbacksignal, wherein the feedback filter includes a noise predictorconfigured to estimate colored noise in an error signal.
 17. Theequalizer of claim 15, wherein the two outputs includes an output signalrepresentative of most likely decoded symbols.
 18. The equalizer ofclaim 17, wherein the most likely decoded symbols are determined basedon trace trellis path metrics maintained by the Viterbi decoder.
 19. Theequalizer of claim 15, and further comprising a block based frequencydomain filter adapted to filter an input signal to provide the filteredinput signal.
 20. The equalizer of claim 15, and further comprising afilter configured to provide a feedback signal.
 21. A system accordingto claim 9, and further comprising a filter configured to provide afeedback signal.
 22. A system according to claim 21, wherein the filterincludes a noise predictor for generating an estimate of colored noisefor adjusting operation of the Viterbi decoder.